• Title/Summary/Keyword: Total Domination Function

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ON THE SIGNED TOTAL DOMINATION NUMBER OF GENERALIZED PETERSEN GRAPHS P(n, 2)

  • Li, Wen-Sheng;Xing, Hua-Ming;Sohn, Moo Young
    • Bulletin of the Korean Mathematical Society
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    • v.50 no.6
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    • pp.2021-2026
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    • 2013
  • Let G = (V,E) be a graph. A function $f:V{\rightarrow}\{-1,+1\}$ defined on the vertices of G is a signed total dominating function if the sum of its function values over any open neighborhood is at least one. The signed total domination number of G, ${\gamma}^s_t(G)$, is the minimum weight of a signed total dominating function of G. In this paper, we study the signed total domination number of generalized Petersen graphs P(n, 2) and prove that for any integer $n{\geq}6$, ${\gamma}^s_t(P(n,2))=2[\frac{n}{3}]+2t$, where $t{\equiv}n(mod\;3)$ and $0 {\leq}t{\leq}2$.

ON MINUS TOTAL DOMINATION OF DIRECTED GRAPHS

  • Li, WenSheng;Xing, Huaming;Sohn, Moo Young
    • Communications of the Korean Mathematical Society
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    • v.29 no.2
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    • pp.359-366
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    • 2014
  • A three-valued function f defined on the vertices of a digraph D = (V, A), $f:V{\rightarrow}\{-1,0,+1\}$ is a minus total dominating function(MTDF) if $f(N^-(v)){\geq}1$ for each vertex $v{\in}V$. The minus total domination number of a digraph D equals the minimum weight of an MTDF of D. In this paper, we discuss some properties of the minus total domination number and obtain a few lower bounds of the minus total domination number on a digraph D.

Characterizations of the Cores of Integer Total Domination Games

  • Kim, Hye-Kyung;Lee, Dae-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.1115-1121
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    • 2007
  • In this paper, we consider cooperative games arising from integer total domination problem on graphs. We introduce two games, rigid integer total domination game and its relaxed game, and focus on their cores. We give characterizations of the cores and the relationship between them.

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SIGNED TOTAL κ-DOMATIC NUMBERS OF GRAPHS

  • Khodkar, Abdollah;Sheikholeslami, S.M.
    • Journal of the Korean Mathematical Society
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    • v.48 no.3
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    • pp.551-563
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    • 2011
  • Let ${\kappa}$ be a positive integer and let G be a simple graph with vertex set V(G). A function f : V (G) ${\rightarrow}$ {-1, 1} is called a signed total ${\kappa}$-dominating function if ${\sum}_{u{\in}N({\upsilon})}f(u){\geq}{\kappa}$ for each vertex ${\upsilon}{\in}V(G)$. A set ${f_1,f_2,{\ldots},f_d}$ of signed total ${\kappa}$-dominating functions of G with the property that ${\sum}^d_{i=1}f_i({\upsilon}){\leq}1$ for each ${\upsilon}{\in}V(G)$, is called a signed total ${\kappa}$-dominating family (of functions) of G. The maximum number of functions in a signed total ${\kappa}$-dominating family of G is the signed total k-domatic number of G, denoted by $d^t_{kS}$(G). In this note we initiate the study of the signed total k-domatic numbers of graphs and present some sharp upper bounds for this parameter. We also determine the signed total signed total ${\kappa}$-domatic numbers of complete graphs and complete bipartite graphs.

A Multiobjective Genetic Algorithm for Static Scheduling of Real-time Tasks (다목적 유전 알고리즘을 이용한 실시간 태스크의 정적 스케줄링 기법)

  • 오재원;김희천;우치수
    • Journal of KIISE:Software and Applications
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    • v.31 no.3
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    • pp.293-307
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    • 2004
  • We consider the problem of scheduling tasks of a precedence constrained task graph, where each task has its execution time and deadline, onto a set of identical processors in a way that simultaneously minimizes the number of processors required and the total tardiness of tasks. Most existing approaches tend to focus on the minimization of the total tardiness of tasks. In another methods, solutions to this problem are usually computed by combining the two objectives into a simple criterion to be optimized. In this paper, the minimization is carried out using a multiobjective genetic algorithm (GA) that independently considers both criteria by using a vector-valued cost function. We present various GA components that are well suited to the problem of task scheduling, such as a non-trivial encoding strategy. a domination-based selection operator, and a heuristic crossover operator We also provide three local improvement heuristics that facilitate the fast convergence of GA's. The experimental results showed that when compared to five methods used previously, such as list-scheduling algorithms and a specific genetic algorithm, the Performance of our algorithm was comparable or better for 178 out of 180 randomly generated task graphs.